PSO - AI Architect

Job Description
Duties and Responsibilities

Job Title:	AI Architect
FSLA:	Exempt
Department:	PSO
Prepared By:	Professional Services
Reports To:	Director, Professional Services
Reviewed Date:
Approved By:

A.     Job Description Objective

LabVantage Enterprise is designed to scale from small, single-site laboratory deployments to complex global enterprises operating across multiple laboratories, geographies, languages, and regulated environments.

The AI Architect is responsible for defining, designing, and guiding the implementation of scalable, secure, and high-quality Artificial Intelligence, Machine Learning, and Generative AI capabilities for LabVantage implementations and related customer solutions. The role combines strong enterprise architecture, technical leadership, product knowledge, and customer engagement skills to translate business requirements into practical AI-enabled solutions.

The AI Architect will work closely with Professional Services, Product Management, R&D, Business Analysts, Project Managers, Engineering, Quality Assurance, Support, and customer stakeholders to ensure AI solutions are aligned with customer needs, LabVantage product capabilities, security expectations, quality standards, and project delivery methodologies.

Experience with Laboratory Information Management Systems, laboratory informatics, and laboratory workflows is highly desirable. However, LIMS experience is good to have but not mandatory . Candidates with strong enterprise AI architecture experience and the ability to understand complex customer domains are encouraged to apply.

The AI Architect is expected to:

·        Participate in customer discovery sessions, design workshops, and technical discussions to understand business requirements, user workflows, data sources, and AI opportunities.

·        Define scalable AI solution architectures using appropriate technologies, models, data sources, integrations, security controls, and deployment patterns.

·        Translate customer requirements into best-practice AI and LabVantage solution designs, balancing configuration, customization, integration, and AI capabilities.

·        Design and guide implementation of Generative AI use cases, including intelligent assistants, document intelligence, knowledge search, Retrieval-Augmented Generation, workflow automation, and AI-driven recommendations.

·        Evaluate the suitability of AI technologies, models, frameworks, and tools based on customer requirements, accuracy, performance, security, maintainability, and cost considerations.

·        Document high-level solution designs, architecture decisions, technical specifications, data flows, AI evaluation approaches, and implementation guidance for project teams.

·        Provide technical leadership and hands-on guidance to implementation teams during design, development, testing, deployment, go-live, and post-go-live support.

·        Establish best practices for AI solution development, including prompt engineering, model evaluation, data governance, observability, guardrails, security, versioning, and monitoring.

·        Ensure AI solutions are designed with appropriate privacy, access-control, auditability, reliability, and responsible-AI considerations.

·        Review AI-enabled applications, integrations, configurations, and technical deliverables to ensure they meet LabVantage and customer quality standards.

·        Partner with LabVantage R&D team to provide feedback on customer requirements, reusable AI capabilities, product enhancements, and emerging market needs.

·        Mentor and coach technical team members on AI architecture, enterprise integration, design best practices, and delivery methodologies.

·        Contribute creative ideas, proof of concepts, reusable components, and process improvements that increase the efficiency and quality of PSO project delivery.

AI and Technical Architecture Expertise

The AI Architect should have strong expertise in the following areas:

·        Generative AI and Large Language Model application architecture

·        Retrieval-Augmented Generation, embeddings, vector search, and knowledge retrieval

·        Prompt engineering, prompt management, model evaluation, guardrails, and hallucination mitigation

·        AI agents, workflow automation, and human-in-the-loop solution design

·        Machine learning and predictive analytics concepts

·        Structured and unstructured data ingestion, transformation, governance, and retrieval

·        Enterprise API integration, web services, event-driven architecture, and system interoperability

·        Cloud platforms, cloud-native architecture, containers, and DevOps/CI/CD concepts

·        Database and data-platform concepts, including relational databases and data security

·        Application architecture, distributed systems, and enterprise software design patterns

·        Java-based application development, web development, JavaScript, SQL, and API technologies

·        AI/ML observability, performance monitoring, quality evaluation, and operational support

Knowledge of the following is desirable:

·        LabVantage LIMS product and configuration capabilities

·        Laboratory information management systems, laboratory informatics, or scientific software

·        Laboratory workflows such as sample management, quality management, stability, instrument interfacing, ELN, LES, and system integration

·        Regulated industries, including life sciences, pharmaceutical, quality, manufacturing, or clinical laboratory environments

·        Amazon Web Services or comparable cloud platforms

·        Docker, containers, and CI/CD technologies

·        Oracle and Microsoft SQL Server

·        Reporting, ETL, and integration tools

·        JBoss, WebLogic, WebSphere, Linux, and enterprise application-server environments

Customer Focus

The AI Architect will build strong working relationships with internal and external customers. The individual must be able to communicate complex technical and AI concepts clearly to business, scientific, and technical stakeholders. The AI Architect will gain customer confidence by understanding customer business and operational needs, setting realistic expectations, identifying risks and alternatives, and designing scalable solutions that create measurable value. The role may also represent LabVantage in customer demonstrations, technical workshops, pre-sales activities, customer training, and industry events.

Architecture Review, Quality, and Delivery

The AI Architect will oversee the design and quality of AI-enabled solutions delivered by project teams. This includes reviewing architecture, code, integrations, prompts, data-access controls, retrieval quality, model outputs, test approaches, and deployment readiness. The primary objective of this review is to ensure that solutions are secure, maintainable, scalable, reliable, and aligned with established technical and AI best practices. The AI Architect will define and continuously improve standards for architecture review, AI quality evaluation, code review, documentation, testing, deployment, and production support.

Project Implementation and Go-Live Support

The AI Architect’s involvement is critical to ensure the appropriate technical framework, resources, automation, security controls, and support model are in place for implementation, testing, go-live, and post-go-live support.

The AI Architect will guide teams in defining test strategies for AI-enabled solutions, including functional testing, integration testing, security testing, regression testing, performance testing, AI output evaluation, and user acceptance testing. The role will help ensure a smooth transition from development and testing environments to production.

Training and Coaching

The AI Architect will provide mentoring and technical leadership to junior and senior engineering team members. This includes reviewing solution designs, encouraging reuse of components, developing delivery best practices, and supporting skill development in AI, GenAI, enterprise architecture, LabVantage implementation, and customer delivery.

Cross-Functional Collaboration

The AI Architect will work across PSO, Product, R&D, Support, Sales, Quality Assurance, and customer teams. The role will provide input on product enhancements, reusable AI capabilities, technical strategy, customer solution patterns, and high-priority issue resolution.

Contribution to Innovation and Reusable Components

The AI Architect will evaluate and propose technical innovations for the PSO organization. This includes developing proof of concepts, AI reference architectures, reusable components, implementation accelerators, evaluation frameworks, and delivery standards that can be used across multiple LabVantage customer projects.

B.     Primary Job Objectives

The table below gives the primary duties/ responsibilities for this position. It shows the expected allotted time over an extended period for the areas supported by the position as well as the Description of those areas.

Rank of Importance	% Allocation	Description
1	60	v   AI Solution Architecture and Customer Delivery: Lead discovery, architecture, design, and delivery of AI-enabled LabVantage solutions. Conduct technical workshops; translate business requirements into scalable technical designs; define AI use cases, integration patterns, data requirements, security controls, and delivery estimates. Provide technical consultation to customers and lead resolution of complex technical issues.
2	30	v   Technical Leadership, Quality, and Collaboration: Establish architecture standards and guide implementation teams. Review solution designs, AI components, code, integrations, testing approaches, and deployment plans. Partner with Business Analysts, Project Managers, R&D, Product, Support, and Sales teams to ensure high-quality delivery and provide feedback for product improvement.
3	10	v   Innovation, Training, and Reusable Assets: Mentor PSO team members; develop AI best practices, reusable solution components, proof of concepts, technical accelerators, and training materials. Participate in technical interviews and contribute to continuous improvement initiatives within PSO.

AI Architect Responsibilities Include the Following:

This is not an exhaustive task list, and other duties may be assigned as deemed appropriate or warranted by the immediate manager.

• Lead AI architecture and solution-design activities for LabVantage customer implementations.
• Conduct technical discovery sessions and architecture workshops with customers and internal project teams.
• Identify practical AI use cases that align with customer business processes, available data, product capabilities, and implementation constraints.
• Define end-to-end architectures for LLM, RAG, AI-agent, machine-learning, intelligent-search, and automation solutions.
• Define agent guardrails, permissions, context management, human approvals, monitoring, evaluation, and error-handling approaches to ensure reliable enterprise operation.
• Design and implement AI agents and multi-agent workflows using LLMs, tools/function calling, APIs, enterprise data sources, and workflow orchestration.
• Design secure integration patterns between LabVantage, enterprise systems, laboratory instruments, document repositories, APIs, and AI services.
• Define data requirements, data-access controls, security considerations, and governance requirements for AI solutions.
• Develop high-level design documents, architecture diagrams, technical specifications, implementation plans, and effort estimates.
• Guide project teams in implementing AI-enabled solutions using established architecture standards and best practices.
• Review code, AI workflows, prompts, retrieval strategies, model outputs, integrations, and deployment configurations.
• Establish quality-evaluation criteria for AI solutions, including accuracy, relevance, reliability, safety, latency, and maintainability.
• Design testing strategies for AI applications, including functional, security, performance, regression, integration, and user acceptance testing.
• Support troubleshooting and resolution of high-priority project, technical, integration, and production issues.
• Provide technical consultation and design guidance to Business Analysts, Project Managers, engineers, and customer stakeholders.
• Collaborate with R&D and Product teams on product defects, enhancement requests, AI opportunities, and reusable product capabilities.
• Support pre-sales activities, solution prototyping, technical demonstrations, and customer presentations as required.
• Create reusable AI components, templates, architectural patterns, accelerators, and documentation for PSO delivery teams.
• Mentor engineering team members on AI technologies, architecture, integration approaches, design patterns, and quality practices.
• Participate in the recruitment and technical evaluation of candidates for relevant technical roles.
• Stay current with developments in AI, machine learning, Generative AI, cloud platforms, enterprise architecture, and laboratory informatics.

C.     Job Qualifications Necessary

·        Bachelor’s degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.

·        Significant progressive experience in enterprise software architecture, application development, data platforms, AI/ML, or Generative AI solution delivery.

·        Demonstrated experience designing and implementing AI or Generative AI applications in enterprise environments.

·        Strong knowledge of LLM application patterns, including RAG, embeddings, vector databases, prompt engineering, guardrails, model evaluation, and agentic workflows.

·        Experience with enterprise integrations, APIs, web services, databases, cloud platforms, and distributed systems.

·        Strong understanding of structured and unstructured data, data pipelines, access control, privacy, and data governance.

·        Hands-on experience building and deploying AI agents or agentic applications, including tool/function calling, agent orchestration, API integration, context management, and workflow automation.

·        Experience evaluating AI-agent quality, reliability, security, latency, cost, and operational performance.

·        Experience with software-development lifecycle practices, including code review, testing, CI/CD, deployment, monitoring, and production support.

·        Working knowledge of Java, JavaScript, SQL, web technologies, and API-based application development is desirable.

·        Ability to translate complex customer requirements into scalable, practical, and well-documented technical solutions.

·        Strong problem-solving, leadership, time-management, decision-making, presentation, and organizational skills.

·        Excellent written and verbal communication skills, with the ability to clearly present and defend technical recommendations to customers and internal stakeholders.

·        Ability to identify process-improvement opportunities and develop efficient, high-quality delivery approaches.

·        Ability and willingness to learn new technologies and business concepts quickly.

Preferred Qualifications

·        Experience with LabVantage, LIMS, laboratory informatics, scientific software, or laboratory automation is strongly preferred but not mandatory.

·        Familiarity with laboratory workflows, including sample management, quality management, stability, instrument interfacing, ELN, LES, and laboratory data management.

·        Experience working in regulated environments where auditability, data integrity, validation, security, and compliance are important.

·        Experience with cloud platforms, container technologies, DevOps, MLOps, or LLMOps.

·        Experience with AWS services, relational databases, vector databases, and enterprise integration technologies.

·        Experience with AI safety, responsible AI, model governance, privacy controls, and human-in-the-loop workflows.

·        Approximately 25% travel may be required.